Abstract
Due to increasing competition caused by globalization manufacturers have to reduce costs and at the same time provide better products to their customers’ individual needs. This can only be done, if the companies are able to understand the behavior of their customers and forecast the sales numbers for their individual products. One way to get a better prognosis of customer behavior patterns are observations on public market places. But the companies have to link together the observations with events influencing the decisions of customers. This can be done by using a decision support system which was developed for retailers in combination with a data warehouse. The experiences from this project can be transferred to manufacturing companies as well, helping them to achieve better planning data for the manufacturing process.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
An C., Fromm H. (eds). (2005). Supply chain management on demand. Berlin, Springer
Becker T. (2005). Prozesse in Produktion und Supply Chain optimieren. Berlin, Springer
BüyüKözkan G., Derelİ T., Baykasoğlu A. (2004). A survey on the methods and tools of concurrent new product development and agile manufacturing. Journal of Intelligent Manufacturing 15(6): 731–751
Dietrich, J. (2004). A rule-based system for eCommerce applications. In Proceedings of knowledge-based intelligent information and engineering systems: 8th international conference. Springer LNCS 3213/2004, Heidelberg, pp. 455–463.
Dillon T.A., Lee R.K., Matheson D. (2005). Value innovation: Passport to wealth creation. Research Technology Management 48(2): 22–36
Kamakura W., Mela C.F., Ansari A., Bodapati A., Fader P., Iyengar R., Naik P., Neslin S., Sun B., Verhoef P.C., Wedel M., Wilcox R. (2005). Choice models and customer relationship management. Marketing Letters 16(3–4): 279–291
Kassel, S., Schumann, C.-A., Grebenstein, K., & Tittmann, C. (2005). A knowledge based decision support system for Ecommerce. Proceedings Euromedia 2005, Toulouse/France.
Kidd P.T. (1994). Agile manufacturing. Reading, Addison-Wesley
Liker J. (2004). The Toyota way. New York, McGraw-Hill
Liu, B., Hsu, W., Han, H.-S., & Xia, Y. (2000). Mining changes for real-life applications. In Y. Kambayashi, M. Mohania, & A. M. Tjoa (Eds.), Data warehousing and knowledge discovery: Second international conference, DaWaK 2000, London, UK, September 2000. Proceedings, LNCS 1874-2000, pp. 337–346.
Salcedo, L. (2004). Market forecast report European commerce, 2003–2009. JupiterResearch, Jupitermedia Corp.
Sol, H. (2002). Expert systems and artificial intelligence in decision support systems. Kluwer Academic Publishers.
Verhoef P.C., Franses P.H., Donkers B. (2002). Changing perceptions and changing behavior in customer relationships. Marketing Letters 13(2): 121–134
Vitt, E. (2002). Business intelligence: Making better decisions faster. Redmond: Microsoft Corporation.
Womack J.P., Jones D.T. (1996). Lean thinking. New York, Simon & Schuster
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kassel, S., Tittmann, C. Implications from customer behavior for manufacturing. J Intell Manuf 18, 475–478 (2007). https://doi.org/10.1007/s10845-007-0050-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-007-0050-8